Group Testing in the Development of an Expanded Cancer Staging System

Though the TNM (Tumor, Lymph Node, Metastasis) is a widely used staging system for predicting the outcome of cancer patients, it is limited in prediction mainly because it does not integrate multiple prognostic factors. Expanding the TNM now becomes possible due to availability of large cancer patient datasets. In this paper, we introduce a group testing algorithm that can be used to add new prognostic factors while preserving the TNM staging system. Our approach starts with survival and evaluates its relation to potential prognostic factors individually and in various combinations. A demonstration is given for lung cancer.

• Type: Conference
• Year: 2008
• Where: ICMLA
• Authors: Dechang Chen, Kai Xing, Donald Henson, Li Sheng
• Keywords: Cancer Patient, ICMLA 2008, Machine Learning, Multiple Prognostic Factors, Prognostic Factors